A digital workshop process decision-making method based on decision tree and expert system

Abstract

The invention relates to a digital workshop process decision-making method based on a decision tree and an expert system, which performs binning processing on the process production data to generate intervalized fuzzy process production data; conducts training and learning on the fuzzy process production data based on a decision tree algorithm, Generate fuzzy rules and import them into the fuzzy rule base; the inference engine is based on the real-time parameter data in the process real-time monitoring database, and performs fuzzy reasoning through interaction with the fuzzy rule base to generate process decisions. The invention conducts training and learning on the process production data of the digital workshop, generates knowledge rules, and then realizes the discovery of process decision-making rules from the daily process production data of the digital workshop, and overcomes the bottleneck of obtaining expert experience knowledge; The added fuzzy facts are matched with the antecedents of the fuzzy rules in the fuzzy rule base, which improves the reasoning speed and avoids the problem of low reasoning efficiency when the number of knowledge rules is large.

Description

technical field [0001] The invention relates to the technical field of digital workshops, in particular to a digital workshop process decision-making method based on a decision tree and an expert system. Background technique [0002] The digital workshop is the comprehensive application of digitalization and network technology in the production workshop. It integrates the information of numerical control equipment and process design system, production organization system and other management systems to form an integrated manufacturing system with comprehensive information flow automation. Due to the industrial characteristics of the digital workshop process, such as various product specifications, complex structure, and high technical difficulty, higher requirements are put forward for the efficiency, stability and reliability of the digital workshop process decision-making, and the intelligent decision-making technology has opened up for this requirement. The new approach, ...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the deficiencies of the prior art, the present invention provides a digital workshop process decision-making method based on a decision tree and an expert system, using a decision tree algorithm to train and learn for the digital workshop process production data, generate knowledge rules, and then realize daily Process decision-making rules are found in process production data to overcome the bottleneck of expert knowledge acquisition; in the reasoning process, only the newly added fuzzy facts in the fact base are matched with the fuzzy rule antecedents in the fuzzy rule base, which improves the reasoning speed. Try to avoid the problem of low reasoning efficiency when the number of knowledge rules is large

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